Article
Engineering, Electrical & Electronic
Paolo Gherardo Carlet, Andrea Favato, Riccardo Torchio, Francesco Toso, Saverio Bolognani, Florian Dorfler
Summary: The data-driven control paradigm overcomes the issues in traditional controller design related to model identification procedures by utilizing raw data directly in control input selection. This article specifically focuses on the data-enabled predictive control algorithm. One major drawback of this algorithm is the increase in online control program complexity with the dimension of the dataset. This becomes particularly important for embedded applications with challenging real-time constraints, such as synchronous motor drives. This work proposes a systematic approach for significantly reducing the complexity of such algorithms, enabling real-time feasibility of the constrained control structure.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Chemistry, Multidisciplinary
Vicente Gutierrez Gonzalez, German Ramos Ruiz, Hu Du, Ana Sanchez-Ostiz, Carlos Fernandez Bandera
Summary: Energy modeling is crucial in analyzing energy conservation measures in buildings, especially in integrating photovoltaic energy. Calibrated building energy models, adjusted based on building properties and meteorological data, are essential for accuracy. Using weather data from third-party companies can bridge the gap between simulated models and measured data, providing a cost-effective solution for reliable building energy models.
APPLIED SCIENCES-BASEL
(2022)
Article
Environmental Sciences
Mirata Hosseini, Anahita Bigtashi, Bruno Lee
Summary: The study illustrates the impacts of building types and design parameters on deviations between typical year weather files and long-term average actual year weather data in terms of energy demand predictions. Certain designs exhibit wider deviations, with a maximum of around 4.5%, suggesting that typical year weather files are still reliable for predicting long-term average energy performance but underestimate peak loads for up to 85% of the time.
Article
Automation & Control Systems
Venkatesh Chinde, Yashen Lin, Matthew J. Ellis
Summary: This paper introduces a data-driven predictive control algorithm for designing controls for building HVAC systems. The algorithm can predict future state trajectories using input/output data from the system without the need for system identification. Through closed-loop simulations and sensitivity analysis, the performance and advantages of the algorithm are demonstrated.
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME
(2022)
Article
Construction & Building Technology
Seon Jung Ra, Jin-Hong Kim, Cheol Soo Park
Summary: This paper presents the application results of model predictive control (MPC) using multiple deep neural network (DNN) models in the cooling system of a factory building. The authors developed 10 simulation models to predict the thermal behavior of the HVAC system and indoor environment. The MPC approach successfully reduces the energy consumption of the condensing units while maintaining the cooling set-point temperature.
ENERGY AND BUILDINGS
(2023)
Article
Energy & Fuels
Rosa Francesca De Masi, Antonio Gigante, Silvia Ruggiero, Giuseppe Peter Vanoli
Summary: This study explores the impact of methodology, site, dataset, and emissions scenario on the numerical evaluation of resilience efficiency measures, using a residential case study in Benevento, Italy. The findings suggest a transition towards a dominant cooling climate due to climate change, which will affect energy balance and the reliability of efficiency measures.
Article
Construction & Building Technology
Adrien Toesca, Damien David, Kevyn Johannes, Michel Lussault
Summary: This paper presents a methodology for producing a minimum set of heatwave weather files that can represent the diversity of expected heatwaves in a specific location. The methodology involves collecting weather projections, identifying heatwaves, constructing a list of indicators, and selecting representative samples of heatwaves. The methodology was tested for Lyon-Saint Exupery Airport, resulting in the identification of 2229 heatwaves within 1260 years of weather projections. The reduced set of 8 representative heatwave weather files can be used for assessing building performance.
BUILDING AND ENVIRONMENT
(2023)
Article
Construction & Building Technology
Pengyuan Shen, Junhuan Liu, Meilin Wang
Summary: The study utilized Urban Weather Generator (UWG) for UHI modeling in the central city area of Shenzhen, with the use of urban morphologic data collected by an information-collection framework and building type classification technique. Through a calibration procedure, the model's error was reduced and results on UHI index and meteorological data changes were obtained.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Energy & Fuels
Shu Chen, Zhengen Ren, Zhi Tang, Xianrong Zhuo
Summary: Buildings globally contribute nearly 40% of total primary energy consumption and 20% of total greenhouse gas emissions. Energy consumption in buildings is on the rise due to increasing world population and living standards, with climate change expected to impact building energy usage significantly. Eastern Australia is projected to experience the most severe temperature increase, affecting heating and cooling energy consumption.
Article
Construction & Building Technology
Luis Sanhudo, Joao Rodrigues, Enio Vasconcelos Filho
Summary: In recent years, tools for building energy analysis and simulation have been developed to improve building energy performance and achieve reliable and accurate energy performance predictions. The study introduces a machine learning methodology using regression algorithms and clustering techniques to rectify erroneous data values and enhance regression models, with viable results.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Tongxin Li, Bo Sun, Yue Chen, Zixin Ye, Steven H. Low, Adam Wierman
Summary: The paper introduces a real-time aggregate flexibility feedback design called Maximum Entropy Feedback (MEF) and a control algorithm, namely Penalized Predictive Control (PPC), which uses reinforcement learning for approximation. The scheme aims to improve communication efficiency, lower computing costs, and demonstrates the optimality of PPC under certain regularity assumptions through examples.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Engineering, Mechanical
N. Tsokanas, R. Pastorino, B. Stojadinovic
Summary: This study proposes a tracking controller for dynamics compensation in real-time hybrid simulations. The controller combines adaptive model predictive control, linear time-varying Kalman filter, and real-time model identification algorithm to adequately compensate for time delays, ensuring high fidelity of the simulations. A virtual motorcycle case study is used to validate the controller's performance and robustness.
MECHANISM AND MACHINE THEORY
(2022)
Article
Construction & Building Technology
Young Sub Kim, Cheol Soo Park
Summary: This paper presents the real-time implementation of model predictive control (MPC) for HVAC systems in an ice-cream factory building. Four artificial neural network (ANN) models were developed to accurately predict the thermal states of the two thermal zones. The real-time MPC approach could save approximately 31.7% of electricity compared to the existing rule-based control.
JOURNAL OF BUILDING PERFORMANCE SIMULATION
(2023)
Article
Thermodynamics
Min Gyung Yu, Gregory S. Pavlak
Summary: Developing intelligent building control strategies has become a multi-objective problem, requiring balancing performance across various factors. Implementing multi-objective optimal controls in buildings is challenging due to complexity and computational burden. This study extracts near-optimal rule sets from a database of non-dominated solutions using multi-objective model predictive control.
Review
Green & Sustainable Science & Technology
Anjukan Kathirgamanathan, Mattia De Rosa, Eleni Mangina, Donal P. Finn
Summary: Managing supply and demand in the electricity grid becomes more challenging with the increasing penetration of variable renewable energy sources. Buildings are expected to have an expanding role in the future smart grid through better grid integration and predictive control. Data-driven predictive control, coupled with the Internet of Things, holds promise for scalable and transferrable approaches in grid integration of buildings.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Thermodynamics
Pengcheng Zhao, Jingang Wang, Liming Sun, Yun Li, Haiting Xia, Wei He
Summary: The production of green hydrogen through water electrolysis is crucial for renewable energy utilization and decarbonization. This research explores the optimal electrode configuration and system design of compactly-assembled industrial electrolyzer. The findings provide valuable insights for industrial application of water electrolysis equipment.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
V. Baiju, P. Abhishek, S. Harikrishnan
Summary: Thermally driven adsorption desalination systems (ADS) have gained attention as an eco-friendly solution for water scarcity. However, they face challenges related to low water productivity and scalability. To overcome these challenges, integrating ADS with other desalination technologies can create a small-scale hybrid system. This study proposes integrating ADS with a Thermo Electric Dehumidification (TED) unit to enhance its performance.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
C. X. He, Y. H. Liu, X. Y. Huang, S. B. Wan, Q. Chen, J. Sun, T. S. Zhao
Summary: A decentralized centroid multi-path RC network model is constructed to improve the temperature prediction accuracy compared to traditional RC models. By incorporating multiple heat flow paths and decentralizing thermal capacity, a more accurate prediction is achieved.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Chaoying Li, Meng Wang, Nana Li, Di Gu, Chao Yan, Dandan Yuan, Hong Jiang, Baohui Wang, Xirui Wang
Summary: There is an urgent need to shift away from heavy dependence on fossil fuels and embrace renewable energy sources, particularly in the energy-intensive oil refining process. This study presents an innovative concept called the Solar Oil Refinery, which applies solar energy in oil refining. A solar multi-energies-driven hybrid chemical oil refining system that utilizes solar pyrolysis and electrolysis has been developed, significantly improving solar utilization efficiency, cracking rate, and hydrogen yield.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Chao Ma, Guanghui Wang, Dingbiao Wang, Xu Peng, Yushen Yang, Xinxin Liu, Chongrui Yang, Jiaheng Chen
Summary: This study proposes a bio-inspired fish-tail wind rotor to improve the wind power efficiency of the traditional Savonius rotor. Through transient simulations and orthogonal experiments, the key factors affecting the performance are identified. A response surface model is constructed to optimize the power coefficient, resulting in an improvement of 9.4% and 6.6% compared to the Savonius rotor.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Sina Bahmanziari, Abbas-Ali Zamani
Summary: This paper proposes a new framework for improving electrical energy harvesting from piezoelectric smart tiles through a combination of magnetic plucking, mechanical impact, and mechanical vibration force mechanisms. Experimental results demonstrate a significant increase in energy yield and average energy harvesting time compared to other mechanisms.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Nanjiang Dong, Tao Zhang, Rui Wang
Summary: This study establishes a multiobjective mixed-variable configuration optimization model for a comprehensive combined cooling, heating, and power energy system, and proposes an efficient generating operator to optimize this model. The experimental results show that the proposed algorithm performs better than other state-of-the-art algorithms.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Ahmed E. Mansy, Eman A. El Desouky, Tarek H. Taha, M. A. Abu-Saied, Hamada El-Gendi, Ranya A. Amer, Zhen-Yu Tian
Summary: This study aims to convert office paper waste into bioethanol through a sustainable pathway. The results show that physiochemical and enzymatic hydrolysis of the waste can yield a high glucose concentration. The optimal conditions were determined using the Box-Behnken design, and a blended membrane was used for ethanol purification.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Sven Klute, Marcus Budt, Mathias van Beek, Christian Doetsch
Summary: Heat pumps are crucial for decarbonizing heat supply, and steam generating heat pumps have the potential to decarbonize the industrial sector. This paper presents the current state, technical and economic data, and modeling principles of steam generating heat pumps.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Le Zhang, To-Hung Tsui, Yen Wah Tong, Pruk Aggarangsi, Ronghou Liu
Summary: This study investigates the effectiveness of a current-carrying-coil-based magnetic field in promoting anaerobic digestion of chicken manure. The results show that the applied magnetic field increases methane yield, decreases carbon dioxide production, and reduces the concentration of ammonia nitrogen. Microbial community analysis reveals the enrichment of certain methanogenic genera and enhanced metabolic pathways. Pilot-scale experiments confirm the technical effectiveness of the magnetic field assistance in enhancing anaerobic digestion of chicken manure.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Bo Chen, Ruiqing Ma, Yang Zhou, Rui Ma, Wentao Jiang, Fan Yang
Summary: This paper presents an advanced energy management strategy for fuel cell hybrid electric heavy-duty vehicles, focusing on speed planning and energy allocation. By utilizing predictive co-optimization control, this strategy ensures safe inter-vehicle distance and minimizes energy demand. Simulation results demonstrate the effectiveness of the proposed method in reducing fuel cell degradation cost and overall operation cost.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Fabio Fatigati, Roberto Cipollone
Summary: Organic Rankine Cycle-based microcogeneration systems that use solar sources to generate electricity and hot water can help reduce CO2 emissions in residential energy-intensive sectors. The adoption of a recuperative heat exchanger in these systems improves efficiency, reduces thermal power requirements, and saves on electricity costs.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Lipeng He, Renwen Liu, Xuejin Liu, Xiaotian Zheng, Limin Zhang, Jieqiong Lin
Summary: This research proposes a piezoelectric-electromagnetic hybrid energy harvester (PEHEH) for low-frequency wave motion and self-sensing wave environment monitoring. The PEHEH shows promising power output and the ability to self-power and self-sense the wave environment.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Shangling Chu, Yang Liu, Zipeng Xu, Heng Zhang, Haiping Chen, Dan Gao
Summary: This paper studies a distributed energy system integrated with solar and natural gas, analyzes the impact of different parameters on its energy utilization and emissions reduction, and obtains the optimal solution through an optimization algorithm. The results show that compared to traditional separation production systems, this integrated system achieves higher energy utilization and greater reduction in carbon emissions.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Qingpu Li, Yaqi Ding, Guangming Chen, Yongmei Xuan, Neng Gao, Nian Li, Xinyue Hao
Summary: This paper proposes and studies a piston-type thermally-driven pump with a structure similar to a linear compressor, aiming to eliminate the high-quality energy consumption of existing pumps and replace mechanical pumps. The coupling mechanism of working fluid flow and element dimension is analyzed based on force analysis, and experimental data analysis is used to determine the pump operation stroke. Theoretical simulation is conducted to analyze the correlation mechanism of the piston assembly. The research shows that the thermally-driven pump can greatly reduce power consumption and has potential for industrial applications.
ENERGY CONVERSION AND MANAGEMENT
(2024)
